Music Ensemble: a large dataset on musicianship, cognition, and personality in musicians and nonmusicians
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The Music Ensemble dataset is a comprehensive, cross-national database detailing musical, cognitive, personality, and demographic profiles of 1438 young adult musicians and nonmusicians (aged 18–30) from 35 research sites across Europe, North America, South America, and Australia. Participants underwent a standardized in-person battery of objective tests measuring verbal, visuospatial, and musical short-term memory, executive functions, nonverbal reasoning, verbal comprehension, and music perception skills. Standardized and custom self-report questionnaires captured music sophistication, music reward, personality traits, socioeconomic status, and demographic characteristics. The dataset includes 678 pair-matched musicians and nonmusicians for age, gender, and education, enabling well-powered investigations into musical expertise and individual differences. The preregistered protocol ensures methodological consistency, making it suitable for rigorous statistical and psychometric research.
Key Metrics & Impact
Leveraging this extensive dataset, we uncover critical insights into human cognition and expertise, offering powerful parallels for enhancing organizational performance and AI development.
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Musicianship Insights
Explores the detailed self-report and objective measures related to musical sophistication, training history, music reward sensitivity, and various music perception skills (Mini-PROMS: Melody, Tuning, Accent, Tempo). Musicians demonstrated significantly higher scores across all these measures, validating the group classification.
Cognitive Performance Analysis
Covers the assessment of verbal, visuospatial, and musical short-term memory (Digit Span, Spatial Span, Melody Span), executive functions (2-back task), nonverbal reasoning (Raven Matrices), and verbal comprehension (WAIS Vocabulary). The dataset allows for detailed analysis of how musical expertise correlates with these cognitive abilities.
Personality Trait Analysis
Details the assessment of personality traits using the Big-Five Inventory-2 (BFI-2), covering Open-mindedness, Conscientiousness, Extraversion, Agreeableness, and Negative Emotionality, including their various facet scales. Internal consistency of these measures was found to be acceptable to good across multiple languages.
Methodology & Data Overview
Outlines the study's preregistered design, standardized data collection protocol across 35 sites, participant inclusion criteria for musicians and nonmusicians, data anonymization, and the detailed structure of the publicly available dataset, including raw and clean files, data dictionary, and processing scripts.
Music Ensemble Study Process Timeline
| Measure | Musicians (Mean) | Nonmusicians (Mean) | Significance (p, d) |
|---|---|---|---|
| Mini-PROMS Total | 26.32 | 19.66 | p<.001, d=1.65 |
| GMSI Active Engagement | 46.38 | 32.81 | p<.001, d=1.58 |
| GMSI Musical Training | 40.88 | 12.94 | p<.001, d=5.36 |
| GMSI Perceptual Abilities | 54.66 | 41.02 | p<.001, d=1.89 |
| GMSI Singing Abilities | 36.29 | 24.28 | p<.001, d=1.69 |
| GMSI General Sophistication | 99.26 | 56.55 | p<.001, d=3.23 |
| Notes: Data derived from Table 10, demonstrating musicians consistently outperform nonmusicians on objective and self-reported musicality measures. | |||
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